Does Gaze Reveal the Human Likeness of an Android?
Takashi Minato∗ , Michihiro Shimada∗ , Shoji Itakura†§ , Kang Lee‡ , and Hiroshi Ishiguro∗§∗ Department of Adaptive Machine Systems, Graduate School of Engineering, Osaka University

2-1 Yamada-oka, Suita, Osaka 565-0871 Japan
Email: minato@ams.eng.osaka-u.ac.jp† Department of Psychology, Graduate School of Letters, Kyoto University
Yoshida Honmachi, Sakyo-ku, Kyoto 606-8501 Japan‡ Department of Psychology, University of California, San Diego
9500 Gilman Drive La Jolla, CA 92093-0109 U.S.A.
§ Intelligent Robotics and Communication Laboratories, Advanced Telecommunications Research Institute International
2-2-2 Hikaridai, Keihanna Science City, Kyoto 619-0288 Japan

I. I NTRODUCTION
Our everyday impressions of intelligence are subjective
phenomena arising from our interactions with other people.
The development of systems that support rich, multimodal
interactions will be of enormous value. Our research goal is to
discover principles underlying natural communication amongindividuals and to establish a methodology for the development of expressive androids. The top-down design of robots
that support natural communication is impossible because
there are no adequate human models. We adopt a constructivist
approach that entails repeatedly developing and integrating
behavioral models, implementing them in humanoid robots,
analyzing their faults, and then improving and reimplementing
them [1].
By following this constructivist approach in a bottom-up
fashion, we have developed a humanoid robot “Robovie”
that has hundreds of situation-dependent behavior modules
and episode rules to govern their combination [2]. This has
allowed us to study how Robovie’s behavior inﬂuences humanrobot communication [3]. However, we may infer that ahumanlike appearance is also important from the fact thathuman beings have evolved specialized neural centers forthe detection and interpretation of human hands and faces.
Human beings also have many biomechanical structures that
support interaction, including scores of muscles for controlling

Healthy human

Familiarity

Abstract— The development of androids that closely resemble
human beings enables us to investigate many phenomena related
to human interaction that could not otherwise be investigatedwith mechanical-looking robots. This is because more humanlike
devices are in a better position to elicit the kinds of responses
that people direct toward each other. In particular, we cannot
ignore the role of appearance in giving us a subjective impressionof human presence or intelligence. However, this impression isinﬂuenced by behavior and the complex relationship between
appearance and behavior. We propose a hypothesis about how
appearance and behavior are related and map out a plan for
android research to investigate the hypothesis. We then examine
a study that evaluates the behavior of androids according to thepatterns of gaze ﬁxations they elicit. Studies such as these, which
integrate the development of androids with the investigationof human behavior, constitute a new research area that fuses
engineering and science.

Uncanny valley

Toy robot

Similarity to human
CorpseFig. 1.

Uncanny valley

facial expressions and the vocal tract, not to mention gestures.
Robovie’s machinelike appearance must have an impact oninteraction, which therefore prevents us from isolating theeffects of behavior. Other studies have also tended to focus
on behavior only, entrusting a robot’s appearance to an artistic
designer. But to isolate the effects of behavior from those of
appearance, it is necessary to develop an android robot thatlooks like a person. Our study tackles the appearance andbehavior problem from the standpoint of both engineering andscience and explores the essence of communication throughthe development of androids.
The android study has two research aspects:• The development of a humanlike robot based on mechanical and electrical engineering, robotics, control theory,
pattern recognition, and artiﬁcial intelligence.
• An analysis of human activity based on the cognitive andsocial sciences.
The two aspects interact with each other closely: to make theandroid humanlike, we must investigate human activity fromthe standpoint of the cognitive, behavioral, and neurosciences,and to evaluate human activity, we need to implement processes that support it in the android.
Research on the development of communication robots has
beneﬁted from insights drawn from the social and life sciences.
However, the contribution of robotics to these ﬁelds has so far
been insufﬁcient in part because conventional humanoid robots
appear mechanical and, therefore, have an impaired ability toelicit interpersonal responses. To provide an adequate testbed
for evaluating models of human interaction, we need robots
that allow us to consider the effects of behavior separatelyfrom those of appearance.
Conversely, research in the social and life sciences generally
takes a humanlike appearance for granted or ignores the issue
of appearance altogether. Thus, its applicability is unclear.
The judicious use of androids in experiments with humansubjects has the potential for overcoming these problems. The
application of androids to the study of human behavior canbe seen as a new research area that fuses engineering andscience in contrast to existing approaches in humanoid robotics
that fail to control for appearance. This paper proposes a
direction for android research based on our hypothesis on therelationship between appearance and behavior. It also reports
a study that evaluates the human likeness of an android basedon human gaze ﬁxations.

Generation of natural motion
Evaluation ofinteraction

Investigation of the appearance
and behavior problem
uncanny valley

synergy hill

Human

S im

ila
r it

yo

fb

Design of methods
for evaluating interaction

Fig. 2.

eh
av
io

r

Human
rance
y of appea
Similarit
Development of humanlike robots

The extended uncanny valley and a map for investigating it.

II. A R ESEARCH M AP BASED ON THE A PPEARANCE AND
B EHAVIOR H YPOTHESIS
A. A Hypothesis about a Robot’s Appearance and Behavior
It may seem that the ﬁnal goal of android development
should be to realize a device whose appearance and behavior
cannot be distinguished from those of a human being (in otherwords, a device that could pass the Total Turing Test at T3[4]). However, since there will always be subcognitive tests
that could be used to detect subtle differences between theinternal architecture of a human being and an android [5], [6],an alternative goal could be to realize a device that is nearly
indistinguishable from human beings in everyday situations.
In the process of pursuing this goal, our research aims toinvestigate principles underlying interpersonal communication.
A signiﬁcant problem for android development is the “uncanny valley,” ﬁrst suggested by Mori [7], [8]. He discussed
the relationship between how similar a robot is to a humanand a subject’s perception of familiarity. A robot’s familiarity
increases with its similarity until a certain point is reachedat which imperfections cause the robot to appear repulsive(Fig. 1). This sudden drop is called an uncanny valley. We areconcerned in our development of androids that these robots
could also fall into the uncanny valley owing to imperfectionsin appearance and behavior. Therefore, a methodology toovercome the uncanny valley is required.
In the ﬁgure, the effect of similarity can be decomposed
into the effects of appearance and behavior, since both interdependently inﬂuence human-robot interaction. We hypothesizethat the relation between appearance and behavior can becharacterized by the graph in Fig. 2 [9]. Figure 2 superimposesgraphs derived from Mori’s “uncanny valley” hypothesis andthe hypothesis that there is a synergistic effect on interaction
when appearance and behavior are well-matched [10]. Simply
put, we hypothesize that an android’s uncanniness can be
mitigated by its behavior, if the behavior closely resembles
that of a person.

Fig. 3.

The android Repliee Q1.

B. Android Research Map
The axes in Fig. 2 are not clearly deﬁned. How do wequantify similarity and how do we evaluate human-robot
interaction? There are three main research issues to deﬁnethem.
a) A method to evaluate human-robot interaction:
Human-robot interaction can be evaluated by its degree of“naturalness.” Therefore, it is necessary to compare humanhuman and human-robot interactions. There are qualitative
approaches to measure a mental state using, for example, thesemantic differential (SD) method. There are also quantitative
methods to observe an individual’s largely unconscious behavior such as gaze behavior, interpersonal distance, and vocal
pitch. These observable responses reﬂect cognitive processes
that we might not be able to infer from answers to a questionnaire. We are studying how a human subject’s responses
reﬂect the humanlike quality of an interaction and how they
relate to the subject’s mental state.
b) Implementing natural motion in androids: To elucidate what kinds of motion make people believe an android’s
behavior to be natural, we endeavor to mimic an individual’s
motion precisely and then monitor how a human subject’s
interaction with the android degrades as we remove some
aspect of the android’s motion. A straightforward way toanimate the android is implementation of the motion of an
actual human subject as measured by a motion capture system.
Most methods that use a motion capture system assume thata human body has the same kinematic structure as a robot

Questioner(Human or Android)

SubjectUp
Up Right

Up Left

Right

Left

Down Right

Down Left

Down(a) The experimental setup

Fig. 5.

Fig. 4.

The android Repliee Q2.

and calculate the joint angles using the robot’s kinematics(e.g., [11]). However, since the kinematic structure of humanand robot differ, there is no guarantee that the robot’s motion
as generated from the angles will resemble human motion.
Therefore, we need a method to ensure that the motions we
see at the surface of the robot resemble those of a humanbeing.
c) The development of humanlike robots: We have developed the android Repliee Q1, shown in Fig. 3. It has 31
degrees of freedom in the upper body and can generate various
kinds of micro motions such as the shoulder movements
typically caused by human breathing. Silicone skin which
has a humanlike feel covers the head, neck, hands, andforearms. The compliance of the air actuators makes for asafer interaction. Highly sensitive tactile sensors mounted justunder the android’s skin enable contact interaction.
Repliee Q1 has now been upgraded to Repliee Q2 shownin Fig. 4. It has 42 degrees of freedom and can make facial
expressions and ﬁnger motions in addition to the movementsof Repliee Q1. The face was molded after a particular Japanese
woman to realize a more humanlike appearance.
We are studying the appearance and behavior problem while
integrating this work. In the next section we present a studyof the appearance and behavior problem based on human gazebehavior during communication.
III. A STUDY OF THE APPEARANCE – BEHAVIOR PROBLEM
A. Breaking eye contact during thinking
In the evaluation of a human-robot interaction, methods ofevaluating a human subject’s (largely unconscious) responses
provide a complementary source of information to insights
gleaned from a questionnaire or focus group. This paper
examines subjects’ gaze behavior. Gaze behavior in humanhuman interaction has been studied in psychology and cognitive science, and gaze behavior in human-robot interaction
can be compared to it.
Breaking eye contact during a conversation has been studiedin psychology. While thinking, people sometimes break eye(b) The discrete eye directions

Experiment scene and eight averted gaze directions

contact (avert their eyes from the interlocutor). There are threemain theories to explain the behavior:• Arousal reduction theory
This theory suggests that individuals break eye contact
while thinking to reduce their arousal and concentrate on
the problem [12].
• The differential cortical activation hypothesis
This hypothesis suggests that brain activation induced bythinking tasks leads individuals to shift their gaze awayfrom the central visual ﬁeld [13].
• Social signal theory
This theory suggests that gaze behavior acts as social
signals; people break eye contact to inform others thatthey are thinking.
If breaking eye contact were a kind of social signal, we
would expect it to be inﬂuenced by the interlocutor. Psychological researchers have reported that there is experimental
evidence to support the social signal theory [14], [15]. We
report an experiment that compares subjects’ breaking of eye
contact with a human and android interlocutor.
We hypothesize that, if the way in which eye contact isbroken while thinking acts as a social signal, subjects willproduce different eye movements if the interlocutor is not
humanlike or if the subjects do not consider the interlocutor to
be a responsive agent. Conversely, if eye movement does notchange, this supports the contention that subjects are treating
the android as if it were a person, or at least a social agent.
B. Experiment 1
1) Procedure: Subjects sit opposite a questioner (Fig. 5 (a)).
Subjects’ eye movements are measured while they are thinking
about the answers to questions posed by the questioner. There
are two types of questions: know questions and think questions.
The know questions are used as a control condition. Subjects
already know the answer to know questions (e.g., “How old
are you?”) but not to think questions because they force thesubject to derive the answer (e.g., “Please tell me a word thatconsists of eight letters.”).
The subjects were asked 10 know questions and 10 thinkquestions in random order. Their faces were videotaped andthe gaze direction was coded beginning from the end of thequestion to the beginning of the answer. We calculated the

Up

Up

20

25
20

Up right

Up right

Up left
15

Knowquestions

5

Right

Left

0

Right

True
answersLieanswers

5

Left
0

Down right
Down right

Up left

10

Thinkquestions10

15

Down left

Down left

Down
Down

Fig. 6. Average percent duration of gaze in eight averted directions forhuman questioner (experiment 1) [%]Fig. 8. Average percent duration of gaze in eight averted directions forhuman questioner (experiment 2) [%]

Up

16

Up

20

Up right

16
12

Up left

8
4

Right

0

Down rightThinkquestions

Up right

Down left
Down

Up left8

Knowquestions
Left

12

Lie
answers

4

Right

0

Down rightTrueanswers

Left

Down left
Down

Fig. 7. Average percent duration of gaze in eight averted directions forandroid questioner (experiment 1) [%]Fig. 9. Average percent duration of gaze in eight averted directions forandroid questioner (experiment 2) [%]average duration of gaze in the eight directions shown in Fig. 5(b).
We prepared two types of questioners: Japanese person(human condition) and the android Repliee Q1 (android condition). To make the android look as humanlike as possible,
we conducted the experiment for the android condition as
follows: A speaker embedded in the android’s chest produced a prerecorded voice. Micro behaviors such as eyeand shoulder movements were implemented in the android
to make it seem natural. At ﬁrst the experimenter sitting
beside the android explained the experiment to the subject tohabituate the subject to the android. The android behaved as anautonomous agent during the explanation (e.g., it continuously
made slight movements of the eyes, heads, and shoulders whileoccasionally yawning). It seemed that the subject believed
the android to be asking questions autonomously, althoughquestions were manually triggered by an experimenter seatedbehind a partition.
The subjects were Japanese adults (six men and six womenin human condition and four men and four women in android
condition). Every subject participated in only one condition.
2) Result: Table I shows the average percentage of time
subjects looked in each eye direction for the human condition,and illustrated by the polar plot in Fig. 6. Table II and Fig. 7
show the results for the android condition in the same manner.

a) Eye contact: A two-sample t-test for the eye contact
duration revealed signiﬁcant effects of question type in bothconditions (t(22) = 1.88, p < 0.05 in the human condition,t(14) = 2.57, p < 0.05 in the android condition). The durationof eye contact for think questions is shorter than that for knowquestions in both conditions. The result is consistent with thecommonsense belief that the time of breaking eye contact
increases while people are thinking. There are no signiﬁcanteffects of the questioner in both question types.
b) Averted eye direction: A 2-way, repeated measuresquestion type (2) × eye direction (8) ANOVA revealed nosigniﬁcant effect in the human condition, but signiﬁcant effectin the android condition (F (1, 112) = 5.74, p < 0.05). There
are no signiﬁcant effects of the questioner in both question
types. Table V summarizes the effects of question type andquestioner in the experiment 1. As can be seen in Fig. 6,
Japanese subjects tend to avert eyes downward when they
are posed a question even if they are not required to derive
the answer. The averted eye direction does not depend on
the question type. It is considered that this gaze behavior isthe standard in Japanese culture. For the android questioner,
however, the averted eye direction changes depending on thequestion type as can be seen in Fig. 7. The subjects looked
around for the think questions frequently compared to theknow questions. The subjects’ mental state in the android

TABLE I
M EAN AND STANDARD DEVIATION OF GAZE DURATION IN EACH DIRECTION FOR HUMAN QUESTIONER ( EXPERIMENT 1) [%]
Mean
Std.
Mean
Std.

Think
Know

Down right
5.42
6.73
5.96
6.43

Down
20.0
17.3
19.0
24.8

Down left
9.29
13.1
2.69
4.07

Right
11.3
11.4
8.25
14.5

Left
16.2
17.3
15.2
12.8

Up right
2.79
4.36
1.83
3.40

Up
2.62
4.66
0.752
1.87

Up left
4.96
6.37
3.05
5.76

Eye contact
27.0
19.3
43.4
23.2

TABLE IIM EAN AND STANDARD DEVIATION OF GAZE DURATION IN EACH DIRECTION FOR ANDROID QUESTIONER ( EXPERIMENT 1) [%]
Mean
Std.
Mean
Std.

Think
Know

Down right
14.1
13.8
6.53
8.26

Down
14.4
13.9
7.57
12.0

Down left
7.23
4.41
7.87
9.77

Right
6.87
7.89
5.10
8.47

Left
16.5
13.3
7.47
7.41

Up right
8.62
14.2
3.73
8.36

Up
4.42
5.93
2.29
5.73

Up left
2.63
2.26
2.18
3.47

Eye contact
25.2
21.0
57.3
28.3

TABLE IIIM EAN AND STANDARD DEVIATION OF GAZE DURATION IN EACH DIRECTION FOR HUMAN QUESTIONER ( EXPERIMENT 2) [%]

Truth
Lie

Mean
Std.
Mean
Std.

Down right
5.22
8.68
0.989
1.82

Down
16.7
18.6
16.0
20.9

Down left
1.12
3.36
3.60
6.74

Right
1.07
2.27
6.00
10.9

Left
15.4
13.7
5.08
7.94

Up right
4.04
11.4
2.25
5.65

Up
6.81
10.4
10.4
12.4

Up left
4.02
6.03
15.9
23.8

Eye contact
45.6
25.5
39.9
29.4

Upside
14.9
16.1
28.5
30.0

TABLE IV
M EAN AND STANDARD OF GAZE DURATION IN EACH DIRECTION FOR ANDROID QUESTIONER ( EXPERIMENT 2) [%]

Truth
Lie

Mean
Std.
Mean
Std.

Down right
2.94
6.63
0.249
0.859

Down
9.94
14.7
13.8
17.6

Down left
1.71
6.62
3.37
5.49

Right
6.31
13.3
9.45
19.3

TABLE VT HE EFFECTS OF QUESTION TYPE AND QUESTIONER ( EXPERIMENT 1)

Eye contact duration
Averted eye direction

Effects of question type
Human
Androidp < .05
p < .05ns
p < .05

Effects of questioner
Think
Know
ns
ns
ns
ns

condition seemed to be different from when they were asked
by a person. According to our hypothesis, this difference
suggests that the subjects consider the android to be a different
kind of agent from a person. Experiment 2 was conducted toobtain evidence to support the above inference.
C. Experiment 2
In experiment 2 we prepared another situation that required
subjects to think about the answer. People generally avoid
eye contact when they deceive an interlocutor, that is, when
they think a lie answer in a conversation. In the experiment aquestioner posed questions to subjects. Subjects were told toanswer either truthfully or dishonestly in advance. The subjects
had to convince the questioner that they were telling the truth
when lying (i.e., to deceive the questioner). We measured
subjects’ eye movements while they were thinking about
the answers. We hypothesized that subjects’ gaze behavior
changes if they do not treat the android as if it were a person.

Left
4.59
7.44
4.31
6.63

Up right
0.0682
0.273
0.00
0.00

Up
0.941
2.58
0.450
1.23

Up left
0.878
2.33
1.26
2.95

Eye contact
72.2
27.0
67.1
30.1

Upside
1.89
3.87
1.71
3.09

1) Procedure: We conducted an experiment almost identical to the one described in section III-B.1 except that subjects
were instructed how to answer the questions. Before asking aquestion subjects were shown a cue card on which the word
TRUTH or LIE was written by an experimenter seated behind apartition. The questioner could not see the card. If the card was
TRUTH (truth answer) subjects were instructed to answer thefollowing question truthfully. If the card was LIE (lie answer)
they were instructed to answer the following question with aconvincing lie. Subjects answered ﬁve questions with truthful answers and ﬁve questions with convincing lie answers.
The questions required personal information to answer (e.g.,“When is your birthday?”) so that the questioner could notknow the truth.
2) Result: Table III shows the average percentage of time
subjects looked in each eye direction for the human condition,and illustrated by the polar plot in Fig. 8. “Upside” in the tables
means a sum of “Up”, “Up right”, and “Up left”. Table IV and
Fig. 9 show the results for the android condition in the samemanner.
a) Answer types: A two-sample t-test for eye contact
duration revealed no signiﬁcant effects of answer type in
the human and android conditions. Furthermore a 2-way,
repeated measures answer type (2) × eye direction (8) ANOVA
revealed no signiﬁcant effect in both conditions. The results

TABLE VI
T HE EFFECTS OF ANSWER TYPE AND QUESTIONER ( EXPERIMENT 2)

Eye contact duration
Averted eye direction

Effects of answer type
Human
Android
ns
ns
ns
ns

Effects of questioner
Truth
Lie
p < .01p < .05
p < .01p < .05

are different from experiment 1. This may be because subjects
tried to show similar reactions in both answer types. The
subjects have succeeded in masking their gaze behavior to
deceive the questioner.
b) Questioner conditions: A two-sample t-test for theeye contact duration revealed signiﬁcant effects of questioner
in both answer types (t(25) = 2.57, p < 0.01 for truthfulanswers, t(25) = 2.34, p < 0.05 for lies). This means thatthe duration of averting their gaze in the human condition islonger than that in the android condition. A 2-way, repeatedmeasures answer type (2) × eye direction (8) ANOVA revealed
the signiﬁcant effect of the questioner in both answer types(F (1, 200) = 6.88, p < 0.01 for truthful answers, F (1, 200) =4.73, p < 0.05 for lies). The subjects especially looked
upward (“Upside” direction) longer for the human questioner
than the android questioner (t(25) = 3.13, p < 0.005 fortruthful answers, t(25) = 3.58, p < 0.001 for lies). Table VIsummarizes the effects of answer type and questioner in theexperiment 2.
The subjects tend to avert eyes downward when they are
posed a question just as with experiment 1. There is nodifference in gaze behavior in the two answer types. However,there is difference for the two questioners.
As can be seen in Fig. 8 and Fig. 9, the subjects frequently
looked around with the human questioner as compared tothe android questioner contrary to the results in experiment
1. Daibo and Takimoto [16] have reported that subjects’body motions (e.g., talking and gaze motion) increase when
they are required to persuade a person of an opinion which
is different from their own opinion. They considered that
subjects have strain or uneasiness owing to their deception
and their unintentional behavior becomes more apparent. Our
results also suggest that subjects had strain against the humanquestioner but not against the android questioner. The subjects
might think that the android questioner could not detect theirdeception. This supports that the subjects are not treating theandroid as if it were a person.
D. Summary
The difference in the gaze behavior with respect to thedifferent questioners suggests that breaking eye contact while
thinking not only is induced by brain activity but has a social
meaning. Comparing the gaze behaviors elicited by the android
and a person is necessary before this evidence is obtained.
Furthermore, it was found that the breaking of eye contact
can be an evaluation of an android’s human likeness. If eye
movement is same as in interpersonal communication, it issuggested that subjects are treating the android as if it were aperson, or at least a social agent. In order to make the results

more persuasive, it is necessary to compare with results fordifferent questioners, such as more machinelike robot.
IV. C ONCLUSION
This paper proposed a hypothesis about how appearance
and behavior are related and mapped out a plan for android research to investigate the hypothesis. The study of breaking eye
contact during thinking was considered from the standpointof the appearance–behavior problem. In the study, we used
the android to investigate the sociality of gaze behavior while
thinking and obtained evidence that differs from psychologicalexperiments in human studies. Furthermore, it was foundthat the breaking of eye contact can be an evaluation of anandroid’s human likeness. This study is only preliminary anda more comprehensive study is needed to explain the resultsin order to contribute to human psychology.
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